6 citations · 11 across the 6 of their papers we have counts for
6 papers
SCOD: From Heuristics to Theory
Vojtech Franc, Jakub Paplham, Daniel Prusa
This paper addresses the problem of designing reliable prediction models that abstain from predictions when faced with uncertain or out-of-distribution samples - a recently propose…
Reject option models comprising out-of-distribution detection
Vojtech Franc, Daniel Prusa, Jakub Paplham
The optimal prediction strategy for out-of-distribution (OOD) setups is a fundamental question in machine learning. In this paper, we address this question and present several cont…
Weight-Reducing Turing Machines
Bruno Guillon, Giovanni Pighizzini, Luca Prigioniero +1
It is well-known that one-tape Turing machines working in linear time are no more powerful than finite automata, namely they recognize exactly the class of regular languages. We pr…
Converting Nondeterministic Two-Way Automata into Small Deterministic Linear-Time Machines
Bruno Guillon, Giovanni Pighizzini, Luca Prigioniero +1
In 1978 Sakoda and Sipser raised the question of the cost, in terms of size of representations, of the transformation of two-way and one-way nondeterministic automata into equivale…
Optimal strategies for reject option classifiers
V. Franc, D. Prusa, V. Voracek
In classification with a reject option, the classifier is allowed in uncertain cases to abstain from prediction. The classical cost-based model of a reject option classifier requir…
Relative Interior Rule in Block-Coordinate Minimization
Tomáš Werner, Daniel Průša
(Block-)coordinate minimization is an iterative optimization method which in every iteration finds a global minimum of the objective over a variable or a subset of variables, while…